Applied Sciences (Aug 2023)
Scene Equipment Saving and Loading Method for Digital Twin Workshop
Abstract
The digital twin workshop contains a vast quantity of heterogeneous data from multiple sources, such as the historical state of workshop equipment, which is essential for analyzing implicit problems and bottlenecks in manufacturing tasks. Nevertheless, the current unidirectional and irreversible time flow of the digital twin workshop makes it difficult to optimize workshop productivity using historical data. This paper proposes a scene equipment saving and loading method for the digital twin workshop to address this issue. The initial steps involve defining a workshop information model which represents multiple pieces of workshop equipment in the virtual space and the content of the data it covers. This model stores data for each object type on the workshop using distinct data structures; a workshop element data saving and loading method is proposed, which can save the historical scene equipment data of the digital twin workshop and load the saved data into the digital twin software; finally, a case study is conducted to determine the data compatibility, the saving and loading efficiency, and the system’s ability to save and load actual workshop scenes. The results demonstrate that this method can efficiently save and load scene equipment data on the workshop, enabling workshop administrators to identify problems and bottlenecks in historical manufacturing tasks and then take steps to increase workshop productivity.
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